Noise rejection in parameters identification for piecewise linear fuzzy models. Simani, S., Fantuzzi, C., Rovatti, R, & Beghelli, S. In Proc. of IEEE International Conference on Fuzzy Systems, FUZZ-IEEE'98, pages 378–383, Anchorage, Alaska, (USA), May, 5-9, 1998. 1998 IEEE International Conference on Fuzzy Systems.
abstract   bibtex   
In this paper the fuzzy model identification problem from noisy data is addressed. The piece-wise linear fuzzy model structure is used as non linear prototype for a multi–input, single–output unknown system. The consequent of the fuzzy model is identified using noisy data, e.g. collected from experiments on real system. The identification procedure is formulated within the Frisch scheme, well established for linear systems, which has been modified and improved to be applied in fuzzy systems field.
@InProceedings{CSR_FUZZ_IEEE:98,
  author = 	 {Simani, S. and Fantuzzi, C. and Rovatti, R and Beghelli, S.},
  title = 	 {Noise rejection in parameters identification for
                  piecewise linear fuzzy models},
  booktitle = 	 {Proc. of {IEEE} International Conference on Fuzzy Systems, {FUZZ-IEEE}'98},
  year = 	 1998,
  organization = {1998 {IEEE} {I}nternational {C}onference on {F}uzzy 
                  {S}ystems},
  address = 	 {Anchorage, {A}laska, (USA)},
  month = 	 {May, 5-9},
  href = {\hyperbibref{fuzz-ieee98.pdf}},
  ID =           199805,
  pages = {378--383},
  ABSTRACT = {  In this paper the fuzzy model identification problem from noisy data
  is addressed. The piece-wise linear fuzzy model structure is used as
  non linear prototype for a multi--input, single--output unknown
  system. The consequent of the fuzzy model is identified using noisy
  data, e.g. collected from experiments on real system.

  The identification procedure is formulated within the Frisch scheme,
  well established for linear systems, which has been modified and
  improved to be applied in fuzzy systems field.}
}

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